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Machine Learning: A Probabilistic Perspective (Adaptive Computation and Machine Learning series)
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What Stands Out
Информация за продукта
- Comprehensive introduction to machine learning using probabilistic models and inference
- Focuses on automated methods of data analysis for detecting patterns and predicting future data
- Covers necessary background material on probability, optimization, and linear algebra
- Discusses recent developments in the field including conditional random fields and deep learning
- Emphasizes principled model-based approach using graphical models
- Includes color images, worked examples, and pseudo-code for algorithms; suitable for upper-level undergraduates and beginning graduate students
| Publisher | The MIT Press |
| Publication date | August 24, 2012 |
| Edition | Illustrated |
| Language | English |
| Print length | 1104 pages |
| ISBN-10 | 0262018020 |
| ISBN-13 | 978-0262018029 |
| Item Weight | 4.14 pounds (1.88 kg) |
| Dimensions | 8.27 x 1.77 x 9.25 inches (21 x 4.5 x 23.5 cm) |
Who Should Buy?
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Graduate Students
Ideal for graduate students pursuing advanced studies in machine learning, offering comprehensive insights and probabilistic approaches.
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Data Scientists
Perfect for data scientists looking to deepen their understanding of probabilistic models and apply them in real-world scenarios.
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Research Professionals
Suitable for researchers in AI and machine learning who need a detailed reference for probabilistic techniques and theories.
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Beginners
Not ideal for beginners due to its complex concepts and mathematical rigor, which may be overwhelming without prior knowledge.
ОПИСАНИЕ НА ПРОДУКТА
Machine Learning: A Probabilistic Perspective (Adaptive Computation and Machine Learning series)
About This Item
Introducing "Machine Learning: A Probabilistic Perspective" - Your Comprehensive Guide to Mastering Machine Learning Concepts and Techniques! Are you keen to delve deep into the world of machine learning? Look no further! Our highlighted product, "Machine Learning: A Probabilistic Perspective," is the ultimate resource you need to understand the intricacies of this cutting-edge technology. Written by renowned experts in the field, this illustrated edition of the popular "Machine Learning: A Probabilistic Perspective" book is part of the Adaptive Computation and Machine Learning series. It explores the key principles, algorithms, models, and applications of machine learning. Whether you’re a beginner or an advanced learner seeking to expand your knowledge, this book has got you covered. This comprehensive guide covers a wide range of topics, including introduction to machine learning, advanced machine learning concepts, and the implementation of machine learning algorithms.
It is designed to provide you with a strong foundation in machine learning theory and equip you with the practical tools necessary for real-world applications. With the help of clear illustrations and examples, you'll gain a deeper understanding of machine learning frameworks and libraries, enabling you to confidently tackle machine learning challenges. This book also discusses the latest trends in the field, keeping you up-to-date with the advancements in machine learning research. Are you interested in applying machine learning to specific domains? "Machine Learning: A Probabilistic Perspective" offers insights into machine learning applications in areas such as healthcare, finance, marketing, e-commerce, computer vision, and more. You'll discover how machine learning techniques can be employed for data analysis, predictive modeling, pattern recognition, natural language processing, image classification, and even fraud detection. Whether you're an aspiring data scientist, a software engineer, or a business professional looking to harness the power of machine learning, this book is an indispensable resource.
It equips you with the knowledge and skills to develop effective machine learning solutions that can revolutionize your industry. Don't miss out on this opportunity to master machine learning! Get your hands on "Machine Learning: A Probabilistic Perspective" now and unlock the endless possibilities of this transformative technology. Start your journey towards becoming a machine learning expert today!.
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Linear Editorial Review
This book is often referred to as the bible of machine learning for good reason. It covers all topics in Considerable depth, providing a solid foundation for anyone looking to begin real work in ML. The author's mathematical explanations are clear and easy to follow, although it should be noted that a reasonably advanced background in estimation theory is required to get the most out of this book. The visual illustrations do an excellent job of explaining concepts that can otherwise be challenging to grasp. The content is heavy on theory, making it more of a reference book than a quick read.
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Професионалисти
- Thorough coverage of all topics
- Clear mathematical explanations
- Excellent visual illustrations
минуси
- Heavy on theory
Product Price History
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